Causal Effect of Count Treatment on Ordinal Outcome Using Generalized Propensity Score: Application to Number of Antenatal Care and Age Specific Childhood Vaccination
It is important to trim GPS when it approaches zero or one without loss of more information due to trimming. Effective sample size after weighting should be used along with other methods such as correlation and absolute standardized mean differences for GPS model selection. GBM should be used for GPS estimation for count treatments. MSM is important for the outcome model when weighting GPS method is used. Finally, the number of antenatal care services had an increasing effect on the probability of age-specific childhood vaccination.
Authors
- Haile Mekonnen Fenta (ORCID: https://orcid.org/0000-0002-3919-2762)
- Zelalem G. Dessie (ORCID: https://orcid.org/0000-0001-9056-6822)
- Temesgen T. Zewotir (ORCID: https://orcid.org/0000-0003-1503-8055)
- Ashagrie Sharew Iyassu
Institutions
- Oulu University Hospital (FI)
- Bahir Dar University (ET)
- Debre Markos University (ET)
- University of KwaZulu-Natal (ZA)
- University of Oulu (FI)
Publication Details
- Journal
- Journal of Epidemiology and Global Health
- Published
- 2025-02-12
- DOI
- https://doi.org/10.1007/s44197-025-00344-7
- Primary Topic
- Advanced Causal Inference Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00